A Statistical Learning Framework for Materials Science: Application to Elastic Moduli of k-nary Inorganic Polycrystalline Compounds

Materials scientists increasingly employ machine or statistical learning (SL) techniques to accelerate materials discovery and design. Such pursuits benefit from pooling training data across, and thus being able to generalize predictions over, k-nary compounds of diverse chemistries and structures. This work presents a SL framework that addresses challenges in materials science applications, where datasets are diverse but of modest size, and extreme values are often of interest. Our advances include the application of power or Hölder means to construct descriptors that generalize over chemistry and crystal structure, and the incorporation of multivariate local regression within a gradient boosting framework. The approach is demonstrated by developing SL models to predict bulk and shear moduli (K and G, respectively) for polycrystalline inorganic compounds, using 1,940 compounds from a growing database of calculated elastic moduli for metals, semiconductors and insulators. The usefulness of the models is illustrated by screening for superhard materials

The Impacts of Persistent Behaviour and Cost Sharing Policy on Demand for Outpatient Visits by the Elderly: Evidence from Taiwan’s National Health Insurance.

[[abstract]]Establishing how to reform the cost-sharing policy to reduce waste in health-care utilisation is an important issue, especially in an ageing society. Using a generalised method of moments (GMM) for the dynamic panel count model during the period 1997–2007 from the National Health Insurance (NHI) programme in Taiwan, this study examines the effects of persistent behaviour and the cost-sharing policy on outpatient medical utilisation for Taiwan’s elderly. Empirically, we find positive and negative coefficient estimations for persistent behaviour and price elasticity, respectively, thereby creating a clear trade-off effect of the cost-sharing policy on health-care utilisation. Furthermore, our study finds that the short-run price elasticity (−0.2561) is always smaller than long-run elasticity (−0.4052). Finally, the empirical results indicate that the price elasticity for females and patients with high medical expenditure, low income, high chronic diseases and good health is higher than that for males and patients with low medical expenditure, high income, low chronic diseases and bad health.[[notice]]補正完